Over the centuries mathematicians have constructed the Theory of Probability, initially using three mathematically pure steps and then adding other ingenious ideas which have been building up over time.
The three steps were:
A—1654—Pascal—Fermat. The famous correspondence between these two established the bases of the theory of probabilities (Pascal discovered the formulas for combinatorial analysis) which is the mathematical core of the concept of risk.
B—In 1703, G. von Leibniz wrote to his friend Jacob Bernoulli, “Nature has established patterns which are the origin of the recurrence of events, but only for the most part”. After twenty years of study this led to Bernoulli's discovery of the “Law of Large Numbers” (“Ars conjectande”—The Art of Conjecturing, 1713). Jacob Bernoulli's theory for the a posteriori calculation of probabilities is empirical since it does not offer a method for organizing all the Discrete Sample Spaces mathematically and for allowing the theoretical probability of their events to be known a priori and exactly. Contrary to the popular idea, the law does not provide a method for validating observed facts, and which are nothing more than the incomplete representation of the total truth.
In essence the law states:
“In any sample the difference between the value observed and its true value will decrease proportionally as the number of observations increases”. A mathematical explanation of the law is therefore needed.
Discrete Sample Spaces—These are all the possible outcomes of an experiment.
Experiment—Experiments are those acts which, when repeated constantly under the same conditions, produce individual results, which we are unable to predict. However, after a certain number of repetitions a defined pattern or regularity will occur. This is the regularity which makes it possible to build an accurate mathematical model with which the experiment can be analyzed.
The lottery draw is a random experiment.
C—In 1773, Abraham de Moivre expounded the structure of normal distribution—“the bell-shaped curve”—and discovered the concept of “standard deviation” (“the doctrine of chances”). De Moivre's success in solving these problems is one of the most important achievements in mathematics. Eighty-three years later, when studying geodetic measurements taken in Bavaria, Gauss arrived at the same conclusion. “A Standard Deviation of 2% is accepted by the majority of statisticians”.
A simple analysis of these three steps shows that the gap which exists has to do with the knowledge of the organization of Sample Spaces, since this is what will allow us to analyze the experiment (lottery drawings) mathematically.
This process is at present carried out using statistics based on observations which have no foundation.
There are Internet sites and pamphlets distributed at Lottery Sales outlets which state, for example:
6 has been drawn 3 times with 27
17 has not appeared in the last 20 drawings
In other words, curious, interesting and casual observations.
Previous mathematical proposals are unknown.
The solution here suggested is based on a methodology which organizes “Discrete Sample Spaces” into patterns. This allows us to calculate the theoretical probability of the events, which are obeyed in the draws. If the calculations of the patterns (or templates) and the facts must coincide (respecting Standard Deviation) then it is possible to make predictions based on this information. A template is produced which represents all the games with the same behavior pattern. These games are represented by colors.
Example
If we play with the following numbers.
010211233645010310213042020312203444040714243342050817283142060718223747070815213246040714243342050817283142060718223747070815213246..................080919293948. . . then we are systematically playing using the same pattern or template, i.e. we always mark 2 numbers in the zero decile, 1 number in the first decile, 1 number in the second decile, 1 number in the third decile and 1 number in the fourth decile.
Each template has its own theoretical probability precisely predetermined and this is obeyed in the drawings. If the calculations and the facts must coincide (respecting Standard Deviation) we can make predictions based on the “search for the probability that an increase in the number of drawings will increase the probability that the observed mean will not deviate more than 2% from the true mean”.
The technical advantages are provided by the computer which shows the statistics of the templates and numbers in a relevant and dynamic way. In any and every lottery the Sample Spaces are dramatically simplified, so that a user need not understand statistics to identify patterns and select high probability numbers for entering in a lottery drawing.
Example
The Super Sena 6-48 type lottery, with 12,271,512 combinations (possible plays) can be represented by only 210 templates, each one with its precise theoretical probability. Therefore it is possible to manage lottery results, given that any game which is played corresponds to one of the templates.
The practical advantage of this is the rationalization of the information, allowing for calculated decisions to be taken. By using colors to represent the patterns (or templates) it is possible to manage the whole system via computer, accessible for example, by a user over the internet.
In 5 years of study and research we can state categorically that everything which exists is based on the observation of past data. This is a criterion not permitted by the law of Large Numbers since this data does not express the whole truth.
The solution we intend to patent is capable of constructive operational variables since it is the result of a precise “mathematical and probabilistic model” and this begins a new phase in our knowledge of the movement of things.
It will become a central tool in any activity involving random movements, such as: genetics, finance, engineering, etc.
The discovery relates theoretical probabilities with facts, since the Law states that the mathematical regularity of an event must be obeyed, i.e., if the theoretical probability of a template is 3%, this means that this pattern should occur about 3 times every 100 draws.
In order to comply with the letter of the law the number of drawings must be the largest possible, but the theoretical probability of any pattern occurring is already sufficiently significant for it to be respected throughout the drawings.
If we compare the information available on the various probabilities of Starts, Types of Sets, Patterns and Numbers, we have a solid base and are therefore well equipped to formulate predictions as to what may happen in the future.
In this we are supported by precise and pertinent information and in accordance with the Law.
The fact that the concepts being used are classic is justification enough for leaving out bibliographic references.
Analysis
When we study any type of observed phenomenon, we have to formulate a Mathematical Model which will help us investigate this phenomenon in a precise way.
In the case of the Cn and p phenomena the challenge initially is to solve the mathematical problem, i.e. find a method which organizes Sample Spaces, whilst meeting the requirements of cause and effect.
Undoubtedly, this is the responsibility of Combinatory Analysis, since the evolution of combinations shows clearly that everything happens in deciles; that is, as basic hypotheses, combinations of deciles themselves and combinations of numbers in the same decile.
A generic solution was used which indicated all the possible combinations, given that we have combinations within combinations.
The colors reveal the forms and when we combine them in an orderly manner in predetermined spaces all the possible types of combination appear.
The resulting system is set out in the form of templates which are the synthesis of the whole natural process.
Following the precise indications given by the colors the systems come together. It is like a symphony.
After the initial harmony, the single notes come in, followed by pairs, then the trines and so forth until the final coming together of the movements.
The hypotheses are confirmed in the first movement and are repeated as in the nature of things.
Templates function as the synthesizer—the catalyst of the system. But we had to understand them in their totality.
Leibniz wrote to Bernoulli:
“Nature has established patterns which give rise to the recurrence of happenings, but only for the most part”.
Up until now there has been no methodology which organizes Sample Spaces in a causal way and which is capable of noticing, even in a simple way, the most obvious and repetitive facts in the world of experience: their patterns of behavior.
The world knows Bernoulli's Law of Large Numbers empirically. It needs an explanation.
But templates are not merely the synthesis. They also constitute the behavior patterns and the establishment of these patterns relies on the precise and a priori calculation of theoretical probabilities.
The template concept demonstrates an extreme logical coherence. Besides indicating the patterns of behavior, it shows that the causes of the occurrence of patterns are the very patterns themselves.
But sets of similar patterns of behavior are not evident in the natural evolution of combinations.
We needed to deduce them, to identify them in the natural assembly and classify them in sets in accordance with similar patterns of behavior.
In the end, the Method gave structure to the system.
Colors are used to produce the various templates, which are defined by the product of the simple combinations which they represent.
The templates rely on patterns of behavior which, when quantified, reveal the Theoretical Probabilities. And all the Sample Spaces become viable.
The basic hypotheses are the perfect answer to the need for a causal explanation (Paul L. Meyer in “Probability—Applications in Statistics”—2nd edition, Chapter 1).
Mathematical Models.
When choosing a model, we can make use of our own critical judgment. This was particularly well expressed by Prof. J. Neyman, who wrote:
“Every time we use Mathematics to study some observed phenomena, we must basically begin by constructing a mathematical model (deterministic or probabilistic) for these phenomena:                1. The model must, inevitably, simplify things.        2. Certain details should be ignored. The good result of the model depends on the fact that the details which have been ignored are (or are not) really of no importance when it comes to explaining the phenomenon being studied.        3. The solution of the mathematical problem may be correct but nevertheless, it might be at total variance with the observed facts, purely because the basic hypotheses have not been confirmed. Generally speaking it is very difficult to state with conviction that a particular mathematical model is suitable or not, before some observation data have been acquired.        4. In order to verify the validity of the model, we must deduce a certain number of consequences from our model and then compare these predicted results with our observations.        
Based on this critical opinion let us examine the Model.
1 Sample Spaces are organized and reduced to groups of templates, or patterns.
ExampleCombinationsGroups of templatesC60,650,063,860 714C80,524,040,0161122C48,612,271,512 210
2 Nothing was ignored
3 The mathematical problem has been correctly solved and the basic hypotheses are fully confirmed, since the mathematical solution of the problem allows for knowledge of all the data of the Sample Spaces
4 There was a mathematical regularity to all the perfectly obeyed consequences.                Predicted results        Standard deviation        Observations        
The model satisfies the above stated requirements (if a series of repetitive experiments agrees with an hypothesis, a law can be stated which governs the phenomenon by means of mathematical derivation and from experimental data).
We would add:
1 The Organization of Sample Spaces must define the behavior patterns and respond to the need for causal explanation.
2 Theoretical Probabilities must be determined both a priori and precisely.
The figures which accompany this patent are taken from the Spanish and French 6-49 type lotteries, showing the behavior of those templates (patterns) which have the same probability. Spain and France have the same type of game (6-49), and therefore the same Theoretical Probability Table.